22 results about "Digital elevation map" patented technology

The invention belongs to the technical field of unmanned aerial vehicle cluster autonomous control and path planning, and particularly discloses an unmanned aerial vehicle cluster three-dimensional collaborative coverage planning method based on multi-subgroup grey wolf optimization, which comprises the following steps: establishing a digital elevation map of a three-dimensional multi-source threat environment, and carrying out environment preprocessing by adopting dynamic Poisson disk sampling and a Voronoi diagram; based on the preprocessed environment, performing balanced task distribution of the unmanned aerial vehicle cluster by using a clustering strategy of sector migration; performing unmanned aerial vehicle cluster global coverage path planning by using an improved multi-subgroup grey wolf optimization algorithm according to a balanced task allocation result, and performing local path optimization based on an adaptive elastic window local greedy method; and performing unmanned aerial vehicle cluster communication and path smooth output based on differential communication to complete unmanned aerial vehicle cluster three-dimensional collaborative coverage planning. According to the invention, the problems of difficulty in reflecting a real working environment, serious track overlapping and non-uniform task load in the prior art are solved.

The invention discloses a distributed waterlogging and ponding digital map prediction system based on edge calculation, and relates to the technical field of urban flood prevention intelligent decision making. The system comprises a distributed intelligent acquisition module, an edge integrated processing module, a multi-stage collaborative analysis module and a visualization and decision output module. Collecting multi-source heterogeneous data through multiple types of sensing equipment; calling a local digital elevation map slice and a lightweight hydrological model, generating local waterlogging state information and self-calibrating model parameters; key information is screened based on double threshold values of information entropy change and accumulated water depth change rate, multi-monitoring-point data and a drainage pipe network topological relation are fused, and regional-level inland inundation situation analysis and accumulated water and recessive water trend prediction are achieved; and generating and updating a whole-region distributed ponding digital map, and outputting graded early warning and auxiliary decision information. According to the method, distributed acquisition and edge calculation are combined, the monitoring real-time performance and precision are improved, and the problems that traditional monitoring is high in delay, low in precision, fuzzy in decision and the like are effectively solved.

The invention discloses a single-frame unmanned aerial vehicle image pixel positioning method and system based on an elevation map, and relates to the technical field of unmanned aerial vehicle image processing and geographic positioning, and the method comprises the steps: obtaining a single-frame original image shot by an unmanned aerial vehicle, unmanned aerial vehicle attitude information during shooting, camera internal and external parameters, and a digital elevation map of a shooting region; according to the internal reference of the camera, converting the pixel coordinate of the target pixel in the original image into a normalized plane coordinate system of the camera, and carrying out coordinate distortion correction to obtain the back projection point coordinate of the target pixel; converting a camera-unmanned aerial vehicle body coordinate system and a body-geographic inertial reference coordinate system according to camera external parameters and unmanned aerial vehicle attitude information to obtain normalized ray direction vectors corresponding to target pixels; an earth surface height constraint is constructed based on a digital elevation map, and an intersection point of a ray and the ground is determined by performing iterative approximation on a space point along a ray direction. According to the invention, rapid and accurate conversion from the single-frame unmanned aerial vehicle image pixel to the geographic coordinate can be realized.

The invention relates to the technical field of multi-mode registration, and discloses a long-distance space registration method and system for a radar photoelectric sensor, and the method comprises the steps: obtaining an initial conversion matrix between a radar coordinate system and a photoelectric sensor coordinate system; preprocessing a target image acquired by a photoelectric sensor in a preset long-distance range to generate photoelectric image feature information; the radar point cloud is mapped to a photoelectric image plane based on the initial conversion matrix, a visual consistency error is calculated based on photoelectric image feature information, and a digital elevation map is utilized to match elevation information of the radar point cloud to calculate an elevation consistency error; and constructing a joint optimization objective function containing dynamic weight distribution of the visual consistency error term and the elevation consistency error term, and solving optimized conversion parameters by minimizing the joint optimization objective function to realize long-distance spatial registration. The method does not need to depend on long-distance target deployment, the implementation cost and the operation difficulty are reduced, and the engineering practicability and the real-time performance are both considered.

The application discloses a kind of single frame unmanned plane image pixel positioning method and system based on elevation map, it is related to unmanned plane image processing and geographic positioning technical field, obtain the single frame original image of unmanned plane shooting and the digital elevation map of the shooting area when unmanned plane attitude information, camera internal and external parameters, shooting;According to camera internal parameter, the pixel coordinates of target pixel in original image are converted to camera normalization plane coordinate system, and target pixel back projection point coordinates are obtained after coordinate distortion correction;According to camera external parameter and unmanned plane attitude information, camera-unmanned plane body coordinate system, body-geographic inertial reference coordinate system conversion is carried out, and the normalized ray direction vector corresponding to target pixel is obtained;Based on digital elevation map, construct ground height constraint, by iterative approximation to space point along ray direction, determine the intersection of ray and ground.The application can realize the fast and accurate conversion of single frame unmanned plane image pixel to geographic coordinate.

This invention provides a method for UAV obstacle avoidance trajectory planning based on digital elevation maps, including digital elevation map conversion, initial trajectory loading, trajectory pre-planning, and trajectory re-planning. Using this invention, UAV obstacle avoidance trajectory planning can fully consider terrain variations during low-altitude flight missions to achieve ground-hugging flight. Simultaneously, this method first performs offline trajectory pre-planning and uploads the planned trajectory to the flight controller to provide flight guidance, effectively solving the problem of low real-time performance. When obstacles or threat areas appear on the pre-planned trajectory, the method provided by this invention can find the vertices of obstacles with complex shapes, handle obstacle overlap issues, and thus quickly plan a flight path.

The application discloses a terrain self-adaptive analysis method and device based on a lunar rover passing adaptation, relates to the technical field of computer software, and comprises the following steps: obtaining a digital elevation map of a target detection area; analyzing the digital elevation map of the target detection area to determine a terrain environment type identification result of the target detection area; determining a lunar rover model currently performing a detection task, and acquiring, according to the lunar rover model, a lunar rover passing physical parameter of the lunar rover currently performing the detection task from a lunar rover parameter database; adaptively allocating a calculation window based on the terrain environment type identification result and the lunar rover passing physical parameter; calculating the slope and the stair height of the target detection area based on the adaptively allocated calculation window to obtain a slope calculation result and a stair height calculation result; and integrating the slope calculation result, the stair height calculation result and the terrain environment type identification result to generate a terrain environment analysis report of the target detection area.

The invention discloses an ecological carbon sink monitoring data processing method and system based on a photovoltaic desertification control mode, and relates to the technical field of image data processing. Collecting cleaning operation and maintenance records, and sorting the cleaning operation and maintenance records according to time to generate a cleaning event table; obtaining array layout data and a digital elevation map, and deducing coverage classification according to the digital elevation map to generate a cleaning influence area map; constructing a cleaning disturbance indication sequence based on the cleaning event table, the cleaning influence area graph and the earth surface feature original sequence; generating a purification weight map based on the cleaning influence area map and the cleaning disturbance indication sequence, and deducting cleaning disturbance components according to the purification weight map to obtain a surface feature purification sequence; obtaining a carbon sink increment evaluation result based on the surface feature purification sequence, the array layout data and the purification weight map; according to the method, accurate identification and quantitative deduction of cleaning disturbance of the photovoltaic power station can be realized, and real ecological changes and operation and maintenance artifacts are clearly distinguished.

The application discloses a star ball vehicle long-distance path planning method and system in a time-varying environment, comprising the following steps: constructing a three-dimensional space-time cost map varying with time based on a digital elevation map and sun position information; in the three-dimensional space-time cost map, expanding nodes in a way that the start point and the end point are taken as targets, nodes are expanded in the spatial dimension and the time dimension at the same time, and the time dimension is unidirectionally increased; searching for a path based on the calculation of the movement cost and the time cost between nodes in the three-dimensional space-time cost map and the principle of minimum cost, to obtain an optimal path; extracting key path points from the optimal path, generating a smooth movement trajectory meeting the kinematic constraints of the star ball vehicle based on the key path points, and generating a navigation point sequence for controlling the movement of the star ball vehicle according to the smooth movement trajectory. The application solves the problem that long-distance path planning is difficult to adapt to the dramatic change of the time-varying environment light, and improves the driving safety and the global path planning ability of the star ball vehicle in a complex time-varying environment.

The invention discloses a planetary vehicle long-distance path planning method and system in a time-varying environment, and the method comprises the steps: constructing a time-varying three-dimensional space-time cost map based on a digital elevation map and sun position information; in the three-dimensional space-time cost graph, a starting point and an ending point are taken as targets, nodes are expanded in the space dimension and the time dimension at the same time, node expansion is carried out in a one-way progressive increase mode of the time dimension, and path search is carried out by calculating the moving cost and the time cost between the nodes based on the three-dimensional space-time cost graph and following the principle of the minimum cost. An optimal path is obtained; key path points are extracted from the optimal path, a smooth movement track meeting the kinematics constraint of the planet vehicle is generated based on the key path points, and a navigation point sequence used for controlling movement of the planet vehicle is generated according to the smooth movement track. According to the invention, the problem that long-distance path planning is difficult to adapt to the dramatic change of illumination in the time-varying environment is solved, and the driving safety and global path planning capability of the planet vehicle in the complex time-varying environment are improved.

The application discloses a vehicle semi-active suspension control method, device, medium and product, relates to the field of vehicle semi-active suspension control, and establishes an equivalent skyhook damping control force model of a target vehicle under random road surface excitation and a suspension preview control model under local feature excitation of a road surface; whether the wheel predicted track of the target vehicle passes through the local feature area of the digital elevation map is judged, the suspension preview control model and the equivalent skyhook damping control force model are switched and used, if yes, the state variables of the target vehicle are used to solve the suspension preview control model by using a model predictive control algorithm, and the damping control force of the adjustable shock absorber is determined; if not, the state variables of the target vehicle and the skyhook damping controller parameters are used to solve the equivalent skyhook damping control force model, and the damping control force of the adjustable shock absorber is determined, so that the semi-active suspension of the target vehicle is controlled. The application improves the control precision of the semi-active suspension of the vehicle.

The application discloses a kind of distributed waterlogging accumulation digital map prediction systems based on edge computing, it is related to urban flood control intelligent decision-making technical field.The system includes distributed intelligent acquisition module, edge integration processing module, multistage collaborative analysis module and visualization and decision output module.Through the acquisition of multiple source heterogeneous data of multiple sensing devices;Call local digital elevation map slice and light hydrological model, generate local waterlogging state information and self-calibrate model parameters;Based on information entropy variation and water depth change rate dual threshold screening key information, fusion multi-monitoring point data and drainage pipe network topological relationship, realize regional waterlogging situation analysis and accumulation water recession trend prediction;Generate and update the distributed water accumulation digital map of whole region, output graded early warning and auxiliary decision information.The application combines distributed acquisition and edge computing, improves monitoring real-time and precision, effectively solves the problems of traditional monitoring, such as high delay, low precision and fuzzy decision.

This invention discloses a trajectory planning method based on dynamic selection of different situations. It loads a digital elevation map (DEM) of a selected area, records the matrix of the DEM with m rows and n columns, and reads relevant parameters of the DEM. The DEM is then converted to grayscale to obtain a grayscale map (map1). A threat area is manually designated to form a threat map (map2). A starting point Ps and an ending point Pe are selected on the DEM for trajectory planning. Based on the parent node Open.k in the Open table, the parent node of each node is found starting from Pe until the starting point Ps is found, generating the final trajectory. By optimizing the data structure and corresponding the parameters of the Open table with the map parameters, the computational load of the trajectory planning algorithm is reduced. Furthermore, the increase in overall computational load after adding other situational weights is minimal, facilitating airborne implementation and solving the technical problem of excessively long computation time in existing trajectory planning methods.

The present application is suitable for the technical field of image processing, and provides a three-dimensional terrain modeling method, device and equipment and storage medium, the method comprising: acquiring a prompt word, inputting the prompt word into a trained terrain map generation model to obtain a target three-dimensional terrain digital elevation map, wherein the terrain map generation model comprises a diffusion model and a quantization decoder connected in sequence, the quantization decoder is used for decoding the RGB image output by the diffusion model into the target three-dimensional terrain digital elevation map, and a target three-dimensional terrain map is generated according to the target three-dimensional terrain digital elevation map, so that three-dimensional terrain modeling can be adaptively performed by acquiring the prompt word, and the present application is simple to use and only needs to input ordinary natural language.

The invention is suitable for the technical field of image processing, and provides a three-dimensional terrain modeling method, device and equipment and a storage medium, and the method comprises the steps: obtaining cue words, inputting the cue words into a trained topographic map generation model, and obtaining a target three-dimensional terrain digital elevation map, the topographic map generation model comprises a diffusion model and a quantization decoder which are connected in sequence, the quantization decoder is used for decoding the RGB image output by the diffusion model into a target three-dimensional topographic digital elevation map, and a target three-dimensional topographic map is generated according to the target three-dimensional topographic digital elevation map, so that three-dimensional topographic modeling can be adaptively carried out by obtaining cue words, and the three-dimensional topographic map generation efficiency is improved. And the scheme is simple to use, and only common natural languages need to be input.

The invention relates to an unmanned platform global path planning and optimizing method in an unstructured environment, and belongs to the technical field of unmanned driving and path planning. The method comprises the following steps: constructing an environment model based on a digital elevation map, extracting terrain gradient information and dividing passable areas; performing path search by adopting an improved A * algorithm, and realizing multi-objective optimization by introducing terrain risk density, elevation cost, gradient cost and rollover stability cost into an evaluation function; by setting a safety threshold and a five-direction search strategy, the safety and efficiency of node selection are improved; and extracting path key points by using a Douglas-Peucker algorithm, and performing path smoothing optimization based on an adaptive Bezier curve to generate a smooth path conforming to the motion constraint of the unmanned platform. According to the method, the safety, stability and search efficiency of path planning are effectively improved, and the method is suitable for autonomous navigation of unmanned platforms in unstructured environments such as cross-country and mountainous regions.

The invention discloses an unmanned aerial vehicle cluster collaborative operation path planning method and device, and belongs to the technical field of unmanned aerial vehicle path planning, and the method comprises the steps: distributing a subtask sequence and a corresponding starting and ending time constraint for each unmanned aerial vehicle in an unmanned aerial vehicle cluster, and obtaining a preliminary operation plan; constructing a three-dimensional digital elevation map model based on the unmanned aerial vehicle cluster operation environment data, and generating a path planning total potential field according to the three-dimensional digital elevation map model; and generating an initial path network diagram based on the path planning total potential field and the three-dimensional digital elevation map model, performing arc weight calculation on the initial path network diagram, and performing path planning on the initial operation plan, the path planning total potential field and the arc weight of the initial path network diagram according to a discrete particle swarm algorithm to obtain an optimal operation path. The method can overcome the defects of a traditional path planning method in a three-dimensional environment, guarantees the safety and stability of the path, and improves the motion controllability of an unmanned aerial vehicle cluster in a three-dimensional space.

The application discloses a typhoon condition large-scale weather prediction downscaling method and system for a wind farm, and a micro-scale database is established through a region segmentation-computation-combination mode based on high-resolution digital elevation maps and roughness data, the computation domain is sequentially calculated according to wind directions after being segmented, an upstream model result is used as a boundary condition for a downstream model, and an overlapping domain flow scaling and interpolation method is used, so that the continuity of the boundary after the combination of each sub-computation domain is ensured, and the influence of the partition computation on the accuracy and continuity of the result is effectively controlled. A new regional dynamic downscaling method is designed, the method realizes long-term numerical simulation with a resolution of dozens of meters in a large region, and effectively reduces the minimum computation resource requirement in the prediction process. In addition to the large-scale weather prediction under the typhoon condition, the method can also be applied to wind power prediction of a wind farm group, and the flexibility and application value are improved.

The invention relates to the technical field of airborne meteorological radars, and discloses an elevation approximate ground clutter suppression method and device for an airborne meteorological radar, which are used for constructing a plurality of pitching center beam stereoscopic scanning systems on an azimuth frame and completely covering the potential ground irradiation range of the airborne meteorological radar. Echo data analysis interception is carried out according to the theoretical grounding range of different pitching center beams, and the height value of each range gate is inversely calculated. A height distribution value in a two-dimensional scanning plane is constructed and is approximate to a digital elevation map. Finally, the terrain heights at different distance gates are obtained, the actually-measured terrain height is measured and calculated according to the aerial carrier speed and the flight time so as to replace a terrain height threshold value selected according to experience in a follow-up interval time, ground clutter suppression calculation is carried out by replacing the terrain height threshold value with the actually-measured terrain height, and the terrain clutter suppression precision is improved. The effect of a digital elevation map is approximately replaced, so that the airborne ground clutter suppression technology can adapt to various complex terrain environments, and the robustness of the ground clutter suppression capability is improved.

The invention discloses an unmanned vehicle global path planning method considering vehicle ground clearance constraint, and belongs to the technical field of unmanned vehicle path planning. The method comprises the following steps: obtaining an original digital elevation map according to open source data, extracting topographic information of the original digital elevation map, and constructing a planning map; performing global path planning on the planning map by using an improved A * algorithm, and mapping a global path to an original digital elevation map; and vehicle basic constraints are introduced by adopting a quadratic optimization method, and optimization of a global path is completed. According to the method, generation of an unsafe path is cut off from the source by considering the ground clearance, so that the driving robustness and reliability of the unmanned vehicle in a complex terrain are fundamentally guaranteed, the risk of'underpinning 'is fundamentally avoided, and the path safety is remarkably improved. The method effectively deals with the uncertainty of the terrain and disturbances such as attitude change of the vehicle in the unstructured terrain, and shows extremely strong engineering robustness.

This invention belongs to the field of autonomous control and path planning technology for unmanned aerial vehicle (UAV) swarms. Specifically, it discloses a three-dimensional collaborative coverage planning method for UAV swarms based on multi-subgroup gray wolf optimization. The method includes establishing a digital elevation map of a three-dimensional multi-source threat environment; preprocessing the environment using dynamic Poisson disk sampling and Voronoi diagrams; based on the preprocessed environment, performing balanced task allocation for the UAV swarm using a sector migration clustering strategy; based on the balanced task allocation results, performing global coverage path planning for the UAV swarm using an improved multi-subgroup gray wolf optimization algorithm, and optimizing local paths using an adaptive elastic window local greedy method; and performing UAV swarm communication and smooth path output based on differential communication to complete the three-dimensional collaborative coverage planning for the UAV swarm. This invention solves the problems of existing technologies, such as difficulty in reflecting the real operating environment, severe track overlap, and uneven task load.